Object Duplicate Research Articles

Энтони Дженкинсон және оның 16 ғасырдағы Орталық Азияның картографиялық схемаларын ревизиясы

The article is devoted to the analysis of a new cartographic scheme of Central Asia of the 16th century, proposed by Anthony Jenkinson in his description of his journey through Russia and Central Asia in 1557–1559 (published in 1589) and in his map compiled with the help of cartographer Clement Adams and based on Russian and English documents, and his own observations. Jenkinson’s new cartographic scheme became widespreaddue to the copies of his map reproduced by many major cartographers, including Gerard Mercator and Abraham Ortelius. The original map was discovered only in the 1980s by the Polish researcher Kristina Szykula. The spatial organization scheme, on the one hand, partially remained true to the graphic line of Ptolemy (where the Oxus flows into the Caspian Sea), and, on the other hand, contained such toponyms as Tartaria, Turchestan, Persia, Corasan, India orientalis, China, Cathaio and Mongol, which had appeared in cartographic space thanks to many travelers. The revolutionary element of this scheme, according to the new positioning of Tashkent, Amu Darya, Syr Darya and Ob, were the following elements: 1) Amu Darya (Oxus) and Syr Darya (Jaxartes) are separated from the Caspian Sea; 2) they are related to Kitaia Lacus; 3) Kitaia Lacus can be interpreted as Aral; 4) Kitaia Lacusis connected with the river Oby (Ob); 5) the river Oby (Ob) is associated with Sur (Syr Darya) and Tashkent; 6) Kitaia Lacus is related to Cathay, which starts immediately east of the Ob and possibly describes not Ming Northern China, but Mongolia.A comparative analysis of the description of the journey and the copies of Jenkinson’s maps has shown the process of incorporating new knowledge about the region into the cartographic space and the stability of old schemes. The resulting compromise solution was reflected on the maps in the form of several layers of information and duplication of individual objects (thus, the Amu Darya is represented on the map twice: as Ougus (Ptolemy’s scheme) and as Amow (Jenkinson’s scheme)), double naming of one object (the Syr Darya acts simultaneously as Oby and as Sur) and deformation of space (Cathay is located near the island of Novaya Zemlya, on the proposed trade route from England to China).

Ce que la reproductibilité fait à la fiction. Imaginaires du diner, modernité industrielle

The diner has become the epitome of post-industrial America in the grip of mass consumerism and is an omnipresent space in twentieth-century American literary and cinematographic fiction, sometimes translated as "roadhouse" or "restaurant". While studies of History and Architecture have already revealed the many issues associated with this space, its functions in novels and films from the 1940s onwards remain to be studied. However, the diner scenes constitute revealing stages for the fictional universe, dependent on the construction of a disoriented modern subject. Based on the duplication and repetition of the same objects and fittings, the reproducibility inherent in the American diner is at the origin of a new relationship to space, conducive to the deployment of the subject’s interiority.

SAM-Net: LiDAR Depth Inpainting for 3D Static Map Generation

Various sensors can be attached and added to autonomous vehicles, included visual cameras, radar, LiDAR (Light Detection And Ranging), and GNSS (Global Navigation Satellite System). These sensors have been studied in many research areas, in particular studies on building precise 3D maps. It is essential for autonomous driving to create an accurate 3D map of the surrounding scene. However, creating an accurate static 3D map is difficult due to changes in moving objects or dynamic environments. Spurious objects on the 3D map can be handled by removing or ignoring them for 3D mapping. Following this idea, we propose an object segmentation and inpainting network. The proposed network called SAM-Net, addresses the object duplication issue by segmenting the objects and inpainting them with the segmentation results. Conventional inpainting research has dealt with RGB images. No matter how well such approaches reconstruct holes or corrupted images, they do not establish 3D points’ relationship with the point cloud frame. Therefore, we suggest a depth inpainting method for outdoor object segmentation and inpainting tasks that utilizes a high-precision depth range sensor (Velodyne HDL-64E), which is not suggested before. Unfortunately, no dataset exists for the outdoor depth inpainting task. Thus, to train our model, we generate a new dataset by locating objects on a clean static background. Moreover, our proposed method shows outstanding depth performance compared to the previous visual inpainting method. Our dataset will be available at: “ <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/JunhyeopLee/lidar_inpainting</uri> ”.

Effect of Image Splicing and Copy Move Forgery on Haralick Features of a Digital Image

Nowadays, digital images have become the fastest way of transferring information, but the existence of advanced photo-editing tools makes it easy to alter digital image content which may be used as proof in a legal case, thus creating a serious problem. The most frequent techniques of image forgery include splicing and copy move. Splicing is an image forgery technique in which, the forger crops a part of the first image and places it in the second image while Copy move forgery is a type of image manipulation that involves copying and pasting at least one component of an image onto other areas of the same image for the purpose of duplication or removal of objects in the image. Finding the integrity of a digital image is critical since it can be used as a legal proof in a multitude of sectors, including investigation of a crime scene. Equally, finding the features of an image that change as a result of image manipulation such as copy move and splicing is very important as this can be used to distinguish between forged and original image. Therefore, in this paper, we looked upon the effect of image splicing and copy move forgery on haralick features of a digital image. CoMoFoD dataset and Images frames extracted from original and spliced videos were used in thisexperiment. The result of this experiment shows that splicing and copy move manipulations have no effect on haralick features of a digital image. As a result, these features cannot be used to tell if an image has been spliced or was manipulated bya copy move forgery

Methodology for eliminating imbalance of image data sets

The methodology of solving the problem of eliminating class imbalance in image data sets is presented. The proposed methodology includes the stages of image fragment extraction, fragment augmentation, feature extraction, duplication of minority objects, and is based on reinforcement learning technology. The degree of imbalance indicator was used as a measure to determine the imbalance of the data set. An experiment was performed using a set of images of the faces of patients with skin rashes, annotated according to the severity of acne. The main steps of the methodology implementation are considered. The results of the classification showed the feasibility of applying the proposed methodology. The accuracy of classification on test data was 85%, which is 5% higher than the result obtained without the use of the proposed methodology. Key words: class imbalance, unbalanced data set, image fragment extraction, augmentation.

Item‐to‐item recommender system with simultaneous use of multiple images for image mosaicking creation in dynamic scenes

Image mosaicking is a series of successive algorithms that use a sequence of images or a video of a scene to create a single image with a wider field of view of the whole scene. In most cases, when dynamic objects exist in the input data, issues, such as ghosting, parallax effects or object duplication, are visible in the resulting mosaic. These technical errors appear when the objects in motion aren't properly treated. In order to create good result mosaics, a new method is presented in this paper. The proposed approach uses all the images at the same time to divide the images into different areas by using k-means clustering to create categories, then each category is recommended from the original images with a recommender system. In fact, by considering each image as a user, each pixel as an item, and each item belonging to a category, it is possible to use a recommender system by computing scores with the item profiles. The resulting mosaic will then be a new user to the system. Furthermore, by clustering the images, projection errors are avoided and a better quality mosaic can be created as is seen in the obtained results.

Rule Extraction Model Based on Decision Dependency Degree

Rule extraction is the core in rough set. Two procedures are contained in rule extraction: one is attribute reduction and another is attribute value reduction. It was proved through computational complexity perspective that obtaining all the reduction, minimum attribute reduction, and minimum attribute value reduction is an NP problem. So, generally, a heuristic reduction method is used to solve attribute reduction and attribute value reduction. However, for most heuristic methods, it is hard to put into practice and has high cost on computational complexity. Moreover, part of the methods extracted redundant rules. To approach a quick and effective model for rule extraction in decision systems, against the concept of distinguishable relation, relevant concepts and basic theorems of rule extraction are proposed. In order to get concise and accurate rules quickly, algorithms for finding conflict object set, finding duplicate object set, and finding redundant rules are given. After that, using decision dependency degree as attribute importance to determine the importance of each attribute in rule object, a new rule extraction model based on decision dependency degree is proposed in this paper. Compared with the previous models, this model does not generate matrix; instead, it finds conflict object set and duplicate object set by equivalence class, and consequently, improves the time performance tomaxOCU,OC2U/C, andOREDU/C/RED2. The theoretical analysis and experimental research show that the new model more accurately and effectively reduces the redundant data and extracts more concise decision rules from dataset.

Defect Tolerance: Fundamental Limits and Examples

This paper addresses the problem of adding redundancy to a collection of physical objects so that the overall system is more robust to failures. In contrast to its information counterpart, which can exploit parity to protect multiple information symbols from a single erasure, physical redundancy can only be realized through duplication and substitution of objects. We propose a bipartite graph model for designing defect-tolerant systems, in which the defective objects are replaced by the judiciously connected redundant objects. The fundamental limits of this model are characterized under various asymptotic settings and both asymptotic and finite-size systems that approach these limits are constructed. Among other results, we show that the simple modular redundancy is in general suboptimal. As we develop, this combinatorial problem of defect tolerant system design has a natural interpretation as one of graph coloring, and the analysis is significantly different from that traditionally used in information redundancy for error-control codes.

Brentano's Mind by Mark Textor

Reviewed by: Brentano's Mind by Mark Textor Carlo Ierna Mark Textor. Brentano's Mind. Oxford: Oxford University Press, 2017. pp. xvi + 302 Cloth, $60.00. Marx Textor's Brentano's Mind begins with a short, illuminating introduction which clearly sets out the author's main aims. The two questions Textor wants to consider are, "What is the nature of mind?" and, "What is the structure of consciousness?" From the outset, Textor explicitly states that his intent is not to provide a historically plausible exegesis of "Brentano's often dense and difficult texts" (6), but to take his "bold, suggestive, and influential" (1) answers to these questions as an inspiration for new systematic analyses. The book is then divided in two parts, corresponding to the two questions. The central concept at stake in the first part is intentionality, or rather "Brentano's thesis" that "all and only mental acts and processes are directed on something" (1). This would imply that intentionality is the "mark of the mental," that is, the feature that allows us to sharply distinguish conscious minds from everything else (technically, a mark of the mental, since there are several [27]). Textor argues that even on the most correct interpretation of intentionality, primitivism (54 and chapter 3), Brentano's thesis cannot be true (87). Instead, as the reader will see in chapter 8, "Husserl's Thesis," namely, something is mental if you can be aware of it without adumbrations (193), would be a better mark of the mental than intentionality. Colors, sounds, and their like always appear as a constant through a system of "modes of presentations" (adumbrations, for example, the same color under different lights), while mental acts do not "appear" through different shadings (179–80). The issue at stake in the second part is the structure of consciousness, which is closely tied to the structure of intentionality. Textor explores the consequences of Brentano's view that one mental act can have several objects, including itself, for contemporary self-representational theories of consciousness. Brentano indeed asserted that every mental act includes its own awareness, without needing a separate introspective act. Textor subsequently addresses the potential objection that this view would lead to an infinite regress. Aristotle provided the original inspiration for Brentano's conception of inner perception as a secondary aspect of every mental act, that is, one that happens, so to speak, alongside any perception. While listening to a piece of music, we are primarily directed to the music, the phenomena of sound, and only secondarily aware of our act of hearing the music. Textor shows in detail how Brentano develops his position by distinguishing between inner perception and inner observation (18). Textor tries to disentangle the various aspects of consciousness in chapter 4: how can we be aware of an object and at the very same time, in, and with, the same act, also be aware of our awareness itself? Brentano's answer is that we cannot be aware of our hearing without being aware of what we hear (112). Hearing and heard are inextricably correlative. There is no duplication of acts and no duplication of objects, that is, we do not hear the same tone twice. There certainly are two objects of any single act, namely, the tone heard and the hearing of the tone (113), the former as the object of the hearing, the latter as the object [End Page 764] of the intrinsic self-awareness of the act. Textor concludes "awareness of hearing F is the same mental act as hearing F" (114), which leads straight into the next chapter, "One Act, Several Conceptual Parts," which in many ways forms the heart of the book. The significance of chapter 5 is nicely prefigured by the epigraph to the whole book: "In a unitary mental activity … there is always a plurality of relations and a plurality of objects." Chapters 5–7 attempt to clarify and disentangle those pluralities. First of all, a unitary mental act is not an assemblage of sub-acts, but we distinguish its conceptual parts through attention and abstraction (122). Secondly, no regress threatens Brentano's account, since an act "neither presents itself as a self-presentation nor has it...

Interactive Videos: Plausible Video Editing using Sparse Structure Points

AbstractVideo remains the method of choice for capturing temporal events. However, without access to the underlying 3D scene models, it remains difficult to make object level edits in a single video or across multiple videos. While it may be possible to explicitly reconstruct the 3D geometries to facilitate these edits, such a workflow is cumbersome, expensive, and tedious. In this work, we present a much simpler workflow to create plausible editing and mixing of raw video footage using only sparse structure points (SSP) directly recovered from the raw sequences. First, we utilize user‐scribbles to structure the point representations obtained using structure‐from‐motion on the input videos. The resultant structure points, even when noisy and sparse, are then used to enable various video edits in 3D, including view perturbation, keyframe animation, object duplication and transfer across videos, etc. Specifically, we describe how to synthesize object images from new views adopting a novel image‐based rendering technique using the SSPs as proxy for the missing 3D scene information. We propose a structure‐preserving image warping on multiple input frames adaptively selected from object video, followed by a spatio‐temporally coherent image stitching to compose the final object image. Simple planar shadows and depth maps are synthesized for objects to generate plausible video sequence mimicking real‐world interactions. We demonstrate our system on a variety of input videos to produce complex edits, which are otherwise difficult to achieve.

Geotag propagation in social networks based on user trust model

In the past few years sharing photos within social networks has become very popular. In order to make these huge collections easier to explore, images are usually tagged with representative keywords such as persons, events, objects, and locations. In order to speed up the time consuming tag annotation process, tags can be propagated based on the similarity between image content and context. In this paper, we present a system for efficient geotag propagation based on a combination of object duplicate detection and user trust modeling. The geotags are propagated by training a graph based object model for each of the landmarks on a small tagged image set and finding its duplicates within a large untagged image set. Based on the established correspondences between these two image sets and the reliability of the user, tags are propagated from the tagged to the untagged images. The user trust modeling reduces the risk of propagating wrong tags caused by spamming or faulty annotation. The effectiveness of the proposed method is demonstrated through a set of experiments on an image database containing various landmarks.

Robust Duplicate Detection of 2D and 3D Objects

In this paper, the authors analyze their graph-based approach for 2D and 3D object duplicate detection in still images. A graph model is used to represent the 3D spatial information of the object based on the features extracted from training images to avoid explicit and complex 3D object modeling. Therefore, improved performance can be achieved in comparison to existing methods in terms of both robustness and computational complexity. Different limitations of this approach are analyzed by evaluating performance with respect to the number of training images and calculation of optimal parameters in a number of applications. Furthermore, effectiveness of object duplicate detection algorithm is measured over different object classes. The authors’ method is shown to be robust in detecting the same objects even when images with objects are taken from different viewpoints or distances.

Direct duplication of physical models in discrete 5-axis machining

This paper deals with the feasibility of direct duplication of physical objects with regard to a classical approach based on reverse engineering. The object surface acquisition is performed using optical devices. Algorithms for tool path generation directly from the cloud of points have been developed in 3-axis machining. A n-buffer simulation completed by the real machining emphasises that direct duplication is efficient in terms of conformity to the geometry. As the surface reconstruction step is removed, the proposed process is faster and simpler to implement. The last step is concerned with the extension to discrete 5-axis machining. The main issue is related to the determination of the part set-ups and the corresponding point cloud segmentation.

Data Partitioning for Parallel Spatial Join Processing

The cost of spatial join processing can be very high because of the large sizes of spatial objects and the computation-intensive spatial operations. While parallel processing seems a natural solution to this problem, it is not clear how spatial data can be partitioned for this purpose. Various spatial data partitioning methods are examined in this paper. A framework combining the data-partitioning techniques used by most parallel join algorithms in relational databases and the filter-and-refine strategy for spatial operation processing is proposed for parallel spatial join processing. Object duplication caused by multi-assignment in spatial data partitioning can result in extra CPU cost as well as extra communication cost. We find that the key to overcome this problem is to preserve spatial locality in task decomposition. In this paper we show that a near-optimal speedup can be achieved for parallel spatial join processing using our new algorithms.

Identifying object isomerism in multidatabase systems

In a multidatabase system that consists of object databases, the same real-world entity can be stored as objects in different databases with incompatible object identifiers. How to identify and integrate these objects representing the same entities such that (a) object duplication in the query result can be avoided, (b) information for the entity can be gathered, and (c) the specialization of multiple classes can be built is an important issue to provide a well structured global object schema and a more informative query result. In this paper, we extend our results on probabilistic query processing and joining relations on incompatible keys to solve the problem. Various data and schema conflicts such as missing data, inconsistent data and domain mismatch which may exist in classes from different databases are considered in the process of identification.